Molecular synaptic profiling of learning-dependent changes in cortical inhabitation

Abstract

Experience can drive both the formation and loss of new synapses, a phenomenon that has been observed in both sensory and motor systems in the mammalian brain. Experiments have typically focused on imaging of excitatory pyramidal neurons in the cerebral cortex, as it has been well-documented that synaptic inputs onto these cells are modified during learning. Over the past decade, it has become clear that synapses from and between molecularly defined subtypes of inhibitory neurons are critical for information processing in the cerebral cortex and that these inhibitory networks play an integral role in circuit plasticity during learning. However, principles for inhibitory synaptic plasticity have been difficult to elucidate, in part because inhibitory synapses comprise only 20% of synapses in the neocortex and inhibitory synapse is an incredibly diverse class, defined by the identity of over a dozen different types of inhibitory neurons connected both to each other and to excitatory neurons in highly specified networks. To understand how inhibitory synaptic plasticity reshapes cortical computations, any analysis of inhibitory synapses and their modification during learning must consider the identity of the pre-and postsynaptic cells. Due to the diversity and scarcity of inhibitory synapses throughout cortical tissue, it has been challenging to use tissue-level biochemical methods to differentiate between classes of inhibitory synapses, let alone study their alterations during learning. In our proposed study, we will develop an innovative synaptic imaging method to chemically transform and physically expand brain tissues 1000-fold, magnifying nanoscale organization of proteins in inhibitory synapses. By combining serial immunostaining, we will perform ultra-multiplexed nanoscale imaging of 60 selected synaptic molecules in targeted inhibitory neurons to enable identification of rare, molecularly specified classes of inhibitory connections and map the changes in the landscape of subtype-specific synapses during a sensory learning task. This work will bring significant mechanistic insights to understanding how the brain reconfigures cortical circuitry to incorporate transient experience, opening a new door to study molecular mechanisms of experience-dependent neural circuit rewiring across brain regions. In addition, the new technology we develop can be broadly used by diverse biological researchers to reveal nanoscale assembly of protein complexes in a wide range of tissue types.

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